Neuroprosthetic devices that electrically stimulate paralyzed muscles provide functional enhancements for individuals with spinal cord injury and stroke such as standing and stepping, reaching and grasping, and bladder and bowel function. Current implanted neuroprosthetic systems utilize considerable external powering and signal processing, and each system is tailored to the specific application for which it was intended. The need to design a customized implant system for each application severely limits progress in the field and delays introduction of new technology to the end user. Therefore, we propose to design, fabricate and evaluate an implanted neuroprosthesis with an open architecture that can be easily configured for current and anticipated neuroprosthetic applications, allows accommodation of new innovations by various participants in the field, minimizes external components, and can be clinically implemented. The implant design we propose is based on a network of small implanted modules, distributed throughout the body. A given system will consist of one or more "hubs" with significant processing capability for implementing advanced control algorithms and an inductive link for external programming and powering, as well as separate input and output "nodes" for sensing and stimulating. The network will initially communicate and distribute power internally using wire-based leads, but the feasibility of a wireless network and local power storage will also be investigated. Power will be provided via an external inductive link, with a rechargeable implanted battery used to provide un-tethered operation. A variety of modules will be developed, each with a specific function including: muscle-based stimulation, nerve cuff stimulation, biopotential (electromyogram, electro-oculogram, electro-encephalogram, electroneurogram) signal recording, body segment orientation measurement and acceleration measurement. Other potential modules that could be incorporated into this system include mechanical actuators, joint angle transduction, and strain gage based sensors. In order to develop a system that maximally exploits advanced technologies while being clinically relevant and commercially viable, we have assembled a team of partners that includes representatives from industry, academia, health care and consumers.